Technical Program Manager, Platform & Runtime Engineering

Tenstorrent•Toronto, ON

2h•$100,000 - $500,000•Hybrid

About The Position

Tenstorrent is seeking a Technical Program Manager within its Platform Gen organization to drive complex, cross-functional engineering initiatives spanning runtime systems, device drivers, deployment, observability, and hardware enablement. The role is hybrid and based in Santa Clara, California; Austin, Texas; or Toronto, Canada. Candidates at various experience levels are welcome; the appropriate level will be assessed during interviews, and offers will align with that level. This is a technical program management role that goes beyond tracking timelines and coordinating meetings. The manager works with software, hardware, systems, and architecture teams to understand technical challenges, identify dependencies, drive solutions, and convert ambiguous engineering problems into clear execution plans. The work supports the reliability and performance of Tenstorrent’s AI platforms, from individual accelerators to large-scale AI compute clusters, and helps improve system reliability, deployment and debugging, software and hardware readiness, and platform support for internal teams and external customers. Compensation for engineers at Tenstorrent ranges from $100,000 to $500,000, including base and variable compensation targets. Actual offers depend on experience, skills, education, background, and location. Employment is contingent on eligibility to access U.S. export-controlled technology and may depend on citizenship or permanent residency status, or the ability to obtain prior license approval.

Requirements

Experience in software engineering, systems engineering, or technical program management in a complex engineering environment.
Ability to understand software architecture, system dependencies, and hardware/software interactions, and translate technical challenges into actionable plans.
Ability to drive ambiguous, cross-functional initiatives involving multiple engineering teams, competing priorities, and evolving requirements.
Data-driven approach and proactivity in identifying risks, investigating issues, and driving problems to resolution.
Hands-on, resourceful approach; strong communication skills; and interest in using code, automation, dashboards, and AI-powered tools to improve engineering workflows.

Responsibilities

Drive end-to-end execution of complex platform engineering initiatives, from problem definition and technical planning through implementation, validation, and delivery.
Coordinate runtime, device driver, deployment, observability, debug tools, hardware, and architecture teams to manage dependencies and unblock engineering progress.
Lead reliability and scalability initiatives for AI systems, including fleet-scale deployment, cluster recovery, hardware/software integration, and resolution of recurring system issues.
Establish execution plans, milestones, success metrics, and reporting mechanisms to help engineering teams identify risks and make informed decisions.
Improve engineering execution using technical problem-solving, telemetry, dashboards, automation, and AI-assisted workflows.
Support platform readiness for new hardware and customer requirements.